• Journal of Korean Society of Transportation
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• v.5 no.1
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• pp.47-58
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• 1987

A commodity distribution problem with intertemporal storage facilities and dynamic transportation networks is proposed. mathematical integer programming methods and multiobjective programming techniques are used in the model formulation. Dynamic characteristics of commodity distribution problems are taken into account in the model formulation. storage facility location problems and transportation link addition problems are incorporated into the intertemporal multicommodity distribution problem. The model is capable of generating the most efficient and rational commodity distribution system. Therefore it can be utilized to provided the most effective investment plan for the transportation infrastructure development as well as to evaluate the existing commodity distribution system. The model determines simultaneously the most efficient locations, sizes, and activity levels of storage facilities as well as new highway links. It is extended to multiobjective planning situations for the purpose of generating alternative investment plans in accordance to planning situations. sine the investment in transportation network improvement yields w\several external benefits for a regional economy, the induced benefit maximization objective is incorporated into the cost minimization objective. The multiobjective model generates explicitly the trade-off between cost savings and induced benefits of the investment in transportation network improvement.

• International Journal of Advanced Culture Technology
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• v.8 no.1
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• pp.165-172
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• 2020

Industrial Revolution means the improvement of productivity through technological innovation and has been a driving force of the whole change of economic system and social structure as the characteristic of technology as the tool of this productivity has changed. Since the first industrial revolution of the 18th century, productivity efficiency has been advanced through three industrial revolutions so far, and this fourth industrial revolution is expected to bring about another revolution of production. In this study, the demand for the introduction of artificial intelligence(AI) technology has been increasing in various business fields due to the rapid development of ICT technology, and the classification of HS(harmonized commodity description and coding system) items has been decided using artificial intelligence technology, which is the core of the fourth industrial revolution. And it is enough to construct HS classification system based on AI technology using inference and deep learning. Performing the HS item classification is not an easy task. Implementation of item classification system using artificial intelligence technology to analyze information of HS item classification which is performed manually by the current person more accurately and without any mistake, And the customs administrations, customs offices, and customs agencies, it is expected to be highly utilized in the innovation of trade practice and the customs administration innovation FTA origin agent.

• The Journal of Asian Finance, Economics and Business
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• v.4 no.4
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• pp.27-37
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• 2017

This study examines the behaviour of staple food price using Multivariate BEKK-GARCH Model. Understanding of staple food price behaviour is important for determining the unpredictability of staple food market and also for policy making. In this paper, we focus on the commodity prices of sugar, rice, soybean and wheat to examine the volatility behaviour of those commodities. The empirical results show that the own-volatility spillover are relatively significant for all food prices. The own-volatility spillover effect for sugar price is relatively large compared with the volatility spillover of other staple food commodities. The findings also highlight that the price volatility of wheat increases during food crisis more than it does when the condition is stable. Also, the own-volatility of rice and wheat in the period of the food crisis is significant and higher compared to the period before food crisis indicates that the past own-volatility effects during food crisis are relatively more difficult to predict because of the uncertainty and high price volatility. Policy recommendations that can be proposed based on the findings are: (1) a better trade agreement in food commodity trade, (2) lower the dependence on wheat importation in Indonesia, and (3) reliable system to minimize food price volatility risks.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.01a
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• pp.75-76
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• 2018

본 논문에서는 상품증권 거래 시스템에 블록체인을 적용하여, 여러 서비스에 거래 시스템을 적용할 수 있게 설계하였다. 블록체인 오픈소스 프레임워크인 Hyperledger를 사용하여 시스템의 안정성을 높였다. 단말기의 배터리 소모량과 네트워크 트래픽을 감소시키기 위한 방식으로 거래소를 적용하는 방법에 관해 기술하였다. 또한, 서드 파티 개발자가 플랫폼을 쉽게 구축할 수 있도록 API 구조를 설계하였다.

• Korea Trade Review
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• v.46 no.5
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• pp.49-63
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• 2021

The HS Convention is an agreement on the harmonized commodity description and coding system enacted by the World Customs Organization in January 1988 to promote international trade and unify the commodity classification systems internationally, and the seventh revision will take effect in January 2022. This study's main purpose is to consider criteria for classifying unmanned autonomous transport systems(UATS) in accordance with Section 17 of the HS nomenclature and to present recommendations for improvement of laws related to tariff classification which may be used to amend related laws in Korea. Currently, there are no provisions within the HS Nomenclature that classify unmanned autonomous transportation systems and equipments. Although such technologies have yet to be commercially deployed, they are being actively developed globally. Thus, this study aims to classify UATS and suggest appropriate amendments to the new edition of the HS Nomenclature and Korean law. This paper examines advance ruling cases from domestic and foreign HS classification under the revision of the HS Convention and the criteria for the classification of UATS and Domestic Korean and foreign classification case studies were investigated, along with a survey of the literature on UATS, in order to derive reasonable tariff classification criteria and present legislative implications. In conclusion, this study aims to provide legislative recommendations for how to improve the system to apply the revisions to the HS Convention to the domestic Korean statutes.

• Korea Trade Review
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• v.44 no.2
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• pp.189-202
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• 2019

The Harmonized System comprises about 5,000 commodity groups; each identified by a six digit code, arranged in a legal and logical structure and is supported by well-defined rules to achieve uniform classification. This study reviews the appropriateness of Korea Customs Service and Tax Tribunal's customs classification decisions concerning the interpretation and application of the Harmonized System for certain ITA goods. Korea Customs Service had classified arbitrary and had not applied in dubio pro reo principle. This paper finds that 57% of Korea Customs Service's classification decisions have erred. Korea government need to take measures to secure uniform interpretation of the HS and its periodic updating in light of developments in technology and changes in trade patterns. This paper suggest to amend customs law and regulation concerning classification committee.

• Korea Trade Review
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• v.47 no.5
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• pp.21-37
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• 2022

Baltic Dry Index (BDI) is difficult to forecast because of the high volatility and complexity. To improve the BDI forecasting ability, this study apply Bayesian variable selection method with a large number of predictors. Our estimation results based on the BDI and all predictors from January 2000 to September 2021 indicate that the out-of-sample prediction ability of the ADL model with the variable selection is superior to that of the AR model in terms of point and density forecasting. We also find that critical predictors for the BDI change over forecasts horizon. The lagged BDI are being selected as an key predictor at all forecasts horizon, but commodity price, the clarksea index, and interest rates have additional information to predict BDI at mid-term horizon. This implies that time variations of predictors should be considered to predict the BDI.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Asia-Pacific Journal of Business
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• v.14 no.1
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• pp.341-350
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• 2023

Purpose - How are gains from trade distributed between countries when economic integration is achieved through free trade? The purpose of this paper is to answer this question. Design/methodology/approach - This study attempts to address the issue of distribution of trade gains between participating countries following economic integration in terms of positive economics. The analysis is therefore based on a theoretical methodology. Findings - First, commodity prices fall and consumer surplus increases in both large and small countries. Second, when economic integration into free trade is achieved, gains from trade always exist in small countries. However, the size of trade gains depends on the degree of difference from the market size of the partner country, the large country. However, the size of the gains from trade depends on the extent of difference between the market size of the large country. If the market size of a large country is much larger and there is a large difference, trade gains will be very large, whereas if the market size is similar, profits of domestic firm will decrease. Therefore, in that case, the size of the gains from trade becomes relatively small because only the gains from exchange exists. On the other hand, in a large country with a large market size, there is a possibility of trade gains only when the market size is similar to that of a small country, which is a trading partner. However, if there is a large difference in market size, the decrease in profits of domestic firm is relatively larger than the increase in consumer surplus due to trade, and rather, a trade loss occurs. Research implications or Originality - Our analysis contributes to filling the gaps in the literature regarding the distribution of gains from trade, and from a policy point of view, it is meaningful in examining the impact of market size, an important variable considered in regional economic integration of countries.

• International Commerce and Information Review
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• v.10 no.4
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• pp.171-199
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• 2008

The purpose of this study is to find out current problems facing the commodity trust of e-marketplace and export channel and product adaptation strategy in e-trade. This study will be an important benchmark to shed the light on understanding export channel and the localization adaptation strategy. The business performance of export corporations in Korea so that they will be able to build their own winning marketing adaptation strategy. This study will also obviously provide Korean export corporations having invested in foreign countries with the solid base to set up their marketing channel and localization adaptation strategy to compete with other export corporations abroad.